• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.39-52
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• 2021

Purpose: Recently, due to increasing usage of high-tech equipment for facility inspection, the need of verifying high-tech equipment is being emphasized. Therefore, the purpose of this paper is to develop performance evaluation methodology of tunnel scanners that inspect tunnel facilities. Method: This paper describes literature reviews regarding the performance evaluation methodology of high-tech based equipment for facility inspection. Based on these investigations and expert advisory meetings, this paper suggests a performance evaluation methodology of tunnel scanner. Result: First evaluation indicator states minimum performance standards of tunnel scanners. Second evaluation indicator is related to tunnel scanner quality. Conclusion: The performance evaluation methodology can provide reliable equipment performance catalogues, helping users to make a proper selection of equipment. Also, developers of equipment can get authorized verification of performances, preventing poor maintenance of facilities.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.57-66
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• 2023

In this paper, a research trend of attack graph studies for Cyber-Physical System (CPS) environments is surveyed, and we analyse the limitations of previous works and prospect the future directions. 35 among around 150 attack graph studies conducted within 5 years target CPS, and we inspect key features of CPS environment in the security aspect. Also, we categorize and analyze target studies in the aspect of modelling physical systems and considering air gaps, which are derived as key features of the security aspects of CPS. Half of 20 research that we surveyed do not reflect those two features, and other studies only consider one of the two features. In this circumstance, we examine challenges that attack graph studies on CPS environment face. Finally, we expect state-led studies or studies targeting open-spec commercial CPS will dominate.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.641-648
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• 2023

Recently, the rapid growth of artificial intelligence among the 4th industrial revolution has progressed based on the performance improvement of semiconductor, and circuit integration. According to transistors, which help operation of internal electronic devices and equipment that have been progressed to be more complicated and miniaturized, the control of heat generation and improvement of heat dissipation efficiency have emerged as new performance indicators. The DUT(Device Under Test) Shell is equipment which detects malfunction transistor by evaluating the durability of transistor through heat dissipation in a state where the power is cut off at an arbitrary heating point applying the rating current to inspect the transistor. Since the DUT shell can test more transistor at the same time according to the heat dissipation structure inside the equipment, the heat dissipation efficiency has a direct relationship with the malfunction transistor detection efficiency. Thus, in this paper, we propose various method for PCB configuration structure to optimize heat dissipation of DUT shell and we also propose various transformation and thermal analysis of optimal DUT shell using computational fluid dynamics.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3260-3267
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• 2023

Zr-Nb alloy have been widely used as fuel rods in nuclear power plants. However, from the Fukushima nuclear accident, the weakness of the rod was revealed under harsh conditions, and research on the safety of these types of rods was conducted after the disaster. The method of depositing chromium onto the existing Zr-Nb alloy fuel rods is being considered as a means by which to compensate for the weakness of Zr-Nb alloy rods because chromium is strong against oxidation at high temperatures and has high strength. In order to secure these advantages, it is important to maintain the Cr thickness of the rods and properly inspect the rods before and during their use in power generation. Eddy current testing is a typical means of evaluating the thickness of thin metals and detecting surface defects. Depending on the size and shape of the inspected object, various eddy current sensors can be applied. In particular, because pancake sensors can be manufactured in very small sizes, they can be used for inspections even in narrow spaces, such as a nuclear fuel assembly. In this study, an eddy current technique was developed to confirm the feasibility of Cr coating thickness evaluations. After determining the design parameters of the pancake sensor by means of a FEM simulation, a FPCB pancake sensor was manufactured and the optimal frequency was selected by measuring minute changes in the Cr-coating thickness using the developed sensor.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.136-144
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• 2022

Construction sites are characterized by dangerous situations and environments that cause fatal accidents. Potential risk detection needs to be improved by continuously monitoring site conditions. However, the current labor-intensive inspection practice has many limitations in monitoring dangerous conditions at construction sites. Computer vision technology that can quickly analyze and collect site conditions from images has been in the spotlight as a solution. Nonetheless, inspection results obtained via computer vision are still stored and managed in centralized systems vulnerable to tampering with information by the central node. Blockchain has been used as a reliable and efficient decentralized information management system. Despite its potential, only limited research has been conducted integrating computer vision and blockchain. Therefore, to solve the current safety management problems, the authors propose a framework for construction site inspection that integrates object detection and blockchain network, enabling efficient and reliable remote inspection. Object detection is applied to enable the automatic analysis of site safety conditions. As a result, the workload of safety managers can be reduced with inspection results stored and distributed reliably through the blockchain network. In addition, errors or forgery in the inspection process can be automatically prevented and verified through a smart contract. As site safety conditions are reliably shared with project participants, project participants can remotely inspect site conditions and make safety-related decisions in trust.

• Journal of Broadcast Engineering
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• v.28 no.3
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• pp.302-313
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• 2023

This paper aims to develop a framework that can fully automate the quality management of training data used in large-scale Artificial Intelligence (AI) models built by the Ministry of Science and ICT (MSIT) in the 'AI Hub Data Dam' project, which has invested more than 1 trillion won since 2017. Autonomous driving technology using AI has achieved excellent performance through many studies, but it requires a large amount of high-quality data to train the model. Moreover, it is still difficult for humans to directly inspect the processed data and prove it is valid, and a model trained with erroneous data can cause fatal problems in real life. This paper presents a dataset reconstruction framework that removes abnormal data from the constructed dataset and introduces strategies to improve the performance of AI models by reconstructing them into a reliable dataset to increase the efficiency of model training. The framework's validity was verified through an experiment on the autonomous driving dataset published through the AI Hub of the National Information Society Agency (NIA). As a result, it was confirmed that it could be rebuilt as a reliable dataset from which abnormal data has been removed.

• Plant Journal
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• v.18 no.4
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• pp.48-57
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• 2023

In this study, I discussed a way of the improved operation criteria to detect combustion instability in advance F-Class Gas Turbine, which adopts lean pre-mixed combustion system. The data of 16 blades path temperature thermocouple installed radially at the gas Turbine exit were collected to analyze the variation of individual blade path temperature. The cumulative variation in individual blade path temperature for one week under normal combustion conditions was confirmed to be up to 26℃. On the other hand, in the event of combustion instability, the symptoms of increased temperature variations in the individual thermocouple were mostly seen from a few days ago. Based on the results of this study, it is deemed appropriate to inspect and maintain in Ulsan Thermal Power Gas Turbine when the individual blade path temperature exceeds 50℃ of the cumulative variation for 10 days.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.17-26
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• 2009

This paper is experimental study to inspect effects of problem solving ability and programming interest using Pico Cricket of the educational robot. The programming learning which is regarded as the very core of information subject improves problem solving ability. But the programming teaming does not display the effects properly, because the programming learning studies a grammar manual. The educational robot has the advantage to approach the programming learning easily for containing entertainment. The Pico Cricket of the educational robot has the advantage not to induce competition but to compose a cooperative learning environment. Also, the Pico Cricket is able to be had interest of programming learning to girl students, because the Pico Cricket is able to suggest life-centered and cooperative contents which girl students like. Accordingly, This paper is study which the programming learning using Pico Cricket affects the problem solving ability and programming interest and men and women's comparison study.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.463-465
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• 2021

Currently, the inspection method printed on food packages and boxes is to sample only a few products and inspect them with human eyes. Such a sampling inspection has the limitation that only a small number of products can be inspected. Therefore, accurate inspection using a camera is required. This paper proposes a deep learning object recognition technology model, which is an artificial intelligence technology, as a method for detecting the defects of expiration date printed on the product packaging. Using the Faster R-CNN (region convolution neural network) model, the color images, converted gray images, and converted binary images of the printed expiration date are trained and then tested, and each detection rates are compared. The detection performance of expiration date printed on the package by the proposed method showed the same detection performance as that of conventional vision-based inspection system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.873-880
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• 2008

When checking the state of deterioration or damage structures, regular visual inspection has very important role. At this point, a visual inspection is performed mainly by sketch or photography with a camera of inspectors. If that happens, it takes a lot of effort and time to inspect appearance damages. The purpose of this study is to develop the automatic recognition system for a more efficient and effective inspection of appearance damages. In the process, the image processing technology and the data management & analysis system for damage recognition are mainly developed and applied. This automatic recognition system enables inspectors or clients to obtain correct data that can recognize a damage, such as, crack, water leakage, efflorescence, delamination (peeling), spalling, etc. In addition, this study takes aim at the effect of secure safety, functional maintenance and extension of design lifetime according to build up continuous and systematic data management system.